By Nate Shames
Nov 3, 2017
I recently had an interesting conversation with my colleague, Zac Levin, concerning the nature and ambitions of social science. We were discussing the attempts over the centuries to establish scientific foundations for the study of social life and behavior, a discussion prompted by a book Zac had read entitled Everybody Lies by Seth Stephens-Davidowitz, an economist whose work is rooted in data analysis. While this may seem to be an abstract piece of intellectual history devoid of connection to the running of a business in the 21st century, I think it led to some important conclusions for business operations and strategy at a time when the tools to increase operational effectiveness are proliferating rapidly.
The business community has been inundated in recent years with near-messianic expectations regarding “big data.” This has come on the heels of some astounding technological innovations that have enabled us to produce and capture more data on more subjects than ever thought possible. Everything from advertising to education to oil and gas exploration to heavy manufacturing have utilized insights from big data to transform their business, and the investments will only continue. This theme gained wide acceptance among the broader public with Kenneth Cukier’s famous Ted Talk entitled Big data is better data. While I don’t dispute Cukier’s central claim, I think a number of caveats are in order.
It is undoubtedly true that the amount of data produced in the world is increasing rapidly alongside our capacity to harness and analyze it, and the big data evangelists are correct to emphasize its enormous potential. But big data is not enough. All the data in the world is worthless unless it can be analyzed properly and be integrated into the decision-making machines that a company has already built. To put it more simply: Big data is not a replacement for good strategy.
Here at Jungle Disk, we use a number of different metrics to capture and analyze a wide range of data. This helps us better understand our business and serve our customers and we take these initiatives very seriously and employ a chief data scientist to help us develop and refine our capabilities in this area. We have seen this pay dividends and will continue to invest in it.
But we also refuse to neglect the traditional practice of strategy. We see big data and corporate strategy as complementary endeavors, not as replacements for one another. While many practitioners and expositors of big data make it seem as though the conclusions are clear, that the right access to data is all that is necessary and once that has been achieved the right decision will be obvious, we at Jungle Disk see the data as merely the beginning. Then the hard work of analysis, interpretation, decision making and execution begins.
And this is where it connects back to my discussion with Zac about the nature of the social sciences. The faith in big data is simply an old dream in new clothing: The dream of establishing a purely scientific foundation for the study of social life. This dream was born out of the rationalism of the Enlightenment and gained its highest expression with the positivism of Auguste Comte and the historical materialism of Karl Marx in the 19th century. The goals of this vast intellectual edifice were nothing less than being able to create a framework enabling man to finally predict and shape human behavior and therefore remove the inconsistencies and false starts and knots endemic to social life. Not a bad goal!
The problem for this dream, of course, is that people are not widgets or rational utility maximizers or any other clean definition or category. Humans are complex and irrational and not captured in their entirety by scientific analysis. Indeed, any attempt to understand human beings wholly through science is bound to fail. And that’s where the qualitative nature of strategy comes into play in our business. It seeks to capture and take into account the messy and irascible parts of human behavior, that which eludes scientific analysis. That’s why big data and strategy must be complementary and not exclusive.